Agent-Based Diagnostic Assistants for Streamlining Primary Care Workflows

Abstract

Primary care faces increasing pressure due to aging populations, rising chronic diseases, and growing demand for efficient services. This article explores a distributed network of AI-powered diagnostic assistants to support primary care physicians in their daily workflows. These intelligent agents operate within ethical boundaries under physician oversight, revolutionizing patient interactions by gathering pre-appointment information, suggesting diagnostic pathways based on symptoms and medical history, and aiding in test result interpretation. The system shows potential to improve efficiency, mitigate physician burnout, and enable faster, more accurate initial diagnoses. Critical implementation considerations include ethical implications, seamless integration with existing Electronic Health Records, and maintaining the physician's role as ultimate decision-maker. This agent-based approach represents a promising evolution in healthcare delivery that preserves human medical expertise while leveraging technological capabilities to address growing demands on primary care systems.